The effective management, storage and retrieval of data continues to be an important task for any computing environment, especially for those environments which process large amounts of information. A fundamental requirement for the effective management of large databases includes source coding (e.g., compression and decompression) of n-dimensional lattice data in order to more efficiently process and store the data. Lattice data includes, for instance, images, signals, volumetric information, etc.
Typically, a distinction is made between lossless and lossy compression techniques. Lossless techniques allow perfect reconstruction of the original data from the compressed data and lossy techniques only allow for the reconstruction of an approximation to the original data from the compressed data.
Many compression techniques also provide multiresolution versions of an image. For example, a low resolution version of the image is provided for visual browsing, while a high resolution version is provided for a hard copy. One example of such a hybrid coding scheme is described in U.S. Pat. No. 5,050,230, entitled "Hybrid Residual-Based Hierarchical Storage and Display Method for High Resolution Digital Images In A Multiuse Environment," issued on Sep. 12, 1991.
Although techniques are available for providing multiresolution versions of an image, a need still exists for an efficient technique for storing and retrieving compressed data, including multiresolution compressed data. A need also exists for a technique that enables an efficient layout of compressed data, such that selected portions of the data can be efficiently retrieved. A further need exists for a compression and retrieval technique that reduces input/output and seek-time bottlenecks during retrieval of the data.